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* @license Apache-2.0
*
* Copyright (c) 2026 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
'use strict';
// MODULES //
var resolveMetricStr = require( '@stdlib/ml/base/kmeans/metric-resolve-str' );
var resolveMetricEnum = require( '@stdlib/ml/base/kmeans/metric-resolve-enum' );
var format = require( '@stdlib/string/format' );
var addon = require( './../src/addon.node' );
// MAIN //
/**
* Assigns each data point in a double-precision floating-point input matrix to its closest centroid using alternative indexing semantics.
*
* @param {NonNegativeInteger} M - number of data points
* @param {NonNegativeInteger} N - number of features
* @param {NonNegativeInteger} k - number of centroids
* @param {string} metric - distance metric
* @param {Float64Array} X - input data matrix
* @param {integer} sx1 - stride of the first dimension of `X`
* @param {integer} sx2 - stride of the second dimension of `X`
* @param {NonNegativeInteger} ox - index offset for `X`
* @param {Float64Array} C - centroid matrix
* @param {integer} sc1 - stride of the first dimension of `C`
* @param {integer} sc2 - stride of the second dimension of `C`
* @param {NonNegativeInteger} oc - index offset for `C`
* @param {Int32Array} out - output array for closest centroid indices
* @param {integer} so - stride length for `out`
* @param {NonNegativeInteger} oo - index offset for `out`
* @param {Int32Array} counts - output array for per-centroid assignment counts
* @param {integer} sco - stride length for `counts`
* @param {NonNegativeInteger} oco - index offset for `counts`
* @throws {TypeError} fourth argument must be a supported distance metric
* @returns {Int32Array} output array
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
* var Int32Array = require( '@stdlib/array/int32' );
*
* var X = new Float64Array( [ 1.0, 1.0, 5.0, 5.0, 1.5, 1.5 ] );
* var C = new Float64Array( [ 1.0, 1.0, 5.0, 5.0 ] );
*
* var out = new Int32Array( 3 );
* var counts = new Int32Array( 2 );
*
* dclosestCentroids( 3, 2, 2, 'sqeuclidean', X, 2, 1, 0, C, 2, 1, 0, out, 1, 0, counts, 1, 0 );
* // out => <Int32Array>[ 0, 1, 0 ]
*/
function dclosestCentroids( M, N, k, metric, X, sx1, sx2, ox, C, sc1, sc2, oc, out, so, oo, counts, sco, oco ) { // eslint-disable-line max-len, max-params
if ( resolveMetricStr( metric ) === null ) {
throw new TypeError( format( 'invalid argument. Fourth argument must be a supported distance metric. Value: `%s`.', metric ) );
}
if ( k < 1 || M < 1 || N < 1 ) {
return out;
}
addon.ndarray( M, N, k, resolveMetricEnum( metric ), X, sx1, sx2, ox, C, sc1, sc2, oc, out, so, oo, counts, sco, oco ); // eslint-disable-line max-len
return out;
}
// EXPORTS //
module.exports = dclosestCentroids;
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